ALTERNATIVE TEST CRITERIA IN COVARIANCE STRUCTURE-ANALYSIS - A UNIFIED APPROACH
ALTERNATIVE TEST CRITERIA IN COVARIANCE STRUCTURE-ANALYSIS - A UNIFIED APPROACH
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DOI：
10.1007/bf02294453
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发表时间：
1989-03-01
期刊：
影响因子：
3
通讯作者：
SATORRA, A
中科院分区：
文献类型：
--
作者：
SATORRA, A
在协方差结构分析的背景下，提供了一个统一的方法来检验参数限制的替代检验准则的渐近理论。讨论发展的一般框架内，区分是否拟合函数是渐近最优的，并允许零假设和备择假设是唯一的近似值的真实模型。此外，信息矩阵的等价物和汇总统计量向量的渐近协方差矩阵允许是奇异的。当拟合函数不是渐近最优时，渐近卡方分布的检验统计量被发展为更经典的检验统计量的自然推广。与功效分析相关的问题，以及与检验相关的统计量的渐近理论，也进行了研究。
In the context of covariance structure analysis, a unified approach to the asymptotic theory of alternative test criteria for testing parametric restrictions is provided. The discussion develops within a general framework that distinguishes whether or not the fitting function is asymptotically optimal, and allows the null and alternative hypothesis to be only approximations of the true model. Also, the equivalent of the information matrix, and the asymptotic covariance matrix of the vector of summary statistics, are allowed to be singular. When the fitting function is not asymptotically optimal, test statistics which have asymptotically a chi-square distribution are developed as a natural generalization of more classical ones. Issues relevant for power analysis, and the asymptotic theory of a testing related statistic, are also investigated.